Sunghoon Ivan Lee

2.1k total citations
87 papers, 1.4k citations indexed

About

Sunghoon Ivan Lee is a scholar working on Rehabilitation, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Sunghoon Ivan Lee has authored 87 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Rehabilitation, 29 papers in Biomedical Engineering and 19 papers in Electrical and Electronic Engineering. Recurrent topics in Sunghoon Ivan Lee's work include Stroke Rehabilitation and Recovery (32 papers), Balance, Gait, and Falls Prevention (18 papers) and Context-Aware Activity Recognition Systems (12 papers). Sunghoon Ivan Lee is often cited by papers focused on Stroke Rehabilitation and Recovery (32 papers), Balance, Gait, and Falls Prevention (18 papers) and Context-Aware Activity Recognition Systems (12 papers). Sunghoon Ivan Lee collaborates with scholars based in United States, South Korea and United Kingdom. Sunghoon Ivan Lee's co-authors include Paolo Bonato, Jie Xiong, Jean‐François Daneault, Dong Li, Majid Sarrafzadeh, Bobak J. Mortazavi, Randie M. Black‐Schaffer, Catherine Adans-Dester, Gloria Vergara-Díaz and Anne O’Brien and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Biomedical Engineering and Archives of Physical Medicine and Rehabilitation.

In The Last Decade

Sunghoon Ivan Lee

79 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sunghoon Ivan Lee United States 23 453 326 257 243 163 87 1.4k
Bert-Jan van Beijnum Netherlands 19 529 1.2× 220 0.7× 135 0.5× 218 0.9× 82 0.5× 101 1.4k
Salvatore Tedesco Ireland 20 443 1.0× 82 0.3× 92 0.4× 216 0.9× 155 1.0× 123 1.7k
Maurizio Schmid Italy 28 1.1k 2.4× 135 0.4× 205 0.8× 238 1.0× 99 0.6× 161 2.4k
Stephen Preece United Kingdom 21 1.0k 2.3× 158 0.5× 110 0.4× 632 2.6× 57 0.3× 64 2.6k
Siti Anom Ahmad Malaysia 23 999 2.2× 194 0.6× 166 0.6× 100 0.4× 77 0.5× 157 2.3k
Giuseppe Vannozzi Italy 26 992 2.2× 213 0.7× 117 0.5× 150 0.6× 122 0.7× 98 2.7k
Laurence Kenney United Kingdom 26 1.8k 3.9× 399 1.2× 157 0.6× 641 2.6× 84 0.5× 111 2.8k
Eduardo Palermo Italy 23 1.0k 2.3× 192 0.6× 130 0.5× 132 0.5× 190 1.2× 89 1.8k
Alberto Borboni Italy 22 565 1.2× 444 1.4× 49 0.2× 107 0.4× 147 0.9× 96 1.5k
Anisoara Paraschiv-Ionescu Switzerland 21 696 1.5× 153 0.5× 76 0.3× 501 2.1× 65 0.4× 53 1.7k

Countries citing papers authored by Sunghoon Ivan Lee

Since Specialization
Citations

This map shows the geographic impact of Sunghoon Ivan Lee's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sunghoon Ivan Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunghoon Ivan Lee more than expected).

Fields of papers citing papers by Sunghoon Ivan Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunghoon Ivan Lee. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sunghoon Ivan Lee. The network helps show where Sunghoon Ivan Lee may publish in the future.

Co-authorship network of co-authors of Sunghoon Ivan Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Sunghoon Ivan Lee. A scholar is included among the top collaborators of Sunghoon Ivan Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sunghoon Ivan Lee. Sunghoon Ivan Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jackson, R.W., et al.. (2025). A Capacitive Backscatter System for Intra-Body Identification. IEEE Journal of Radio Frequency Identification. 9. 308–319.
2.
Li, Zhaoying, Ginger E. Nicol, David C. Mohr, et al.. (2025). Satisfaction, user experiences, and initial efficacy of a technology-supported self-management intervention (iSMART) to improve post-stroke functioning: a remoted randomized controlled trial. Topics in Stroke Rehabilitation. 32(7). 677–691. 2 indexed citations
3.
LaVela, Sherri L., Charles H. Bombardier, Mandy W.M. Fong, et al.. (2025). Topic: Evaluation and Treatment of Social Isolation and Loneliness: Evidence-based Recommendations for Stroke and Neurological Rehabilitation. Current Physical Medicine and Rehabilitation Reports. 13(1).
4.
5.
Li, Zhaoying, Ginger E. Nicol, David C. Mohr, et al.. (2024). A Digital Intervention to Promote Self-Management Self-Efficacy Among Community-Dwelling Individuals With Stroke: Pilot Randomized Controlled Trial. JMIR Rehabilitation and Assistive Technologies. 11. e50863–e50863. 6 indexed citations
6.
Lee, Sunghoon Ivan, Yunda Liu, Gloria Vergara-Díaz, et al.. (2024). Wearable-Based Kinematic Analysis of Upper-Limb Movements During Daily Activities Could Provide Insights into Stroke Survivors’ Motor Ability. Neurorehabilitation and neural repair. 38(9). 659–669. 2 indexed citations
7.
Lee, Sunghoon Ivan, et al.. (2024). GoalTrack: Supporting Personalized Goal-Setting in Stroke Rehabilitation with Multimodal Activity Journaling. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 8(4). 1–29. 1 indexed citations
8.
Lee, Sunghoon Ivan, et al.. (2023). Detection and Assessment of Point-to-Point Movements During Functional Activities Using Deep Learning and Kinematic Analyses of the Stroke-Affected Wrist. IEEE Journal of Biomedical and Health Informatics. 28(2). 1022–1030. 5 indexed citations
9.
Wong, Alex, Mandy W.M. Fong, Christopher Metts, et al.. (2023). Using Intervention Mapping and Behavior Change Techniques to Develop a Digital Intervention for Self-Management in Stroke: Development Study. JMIR Human Factors. 10. e45099–e45099. 11 indexed citations
10.
11.
Xiong, Jie, Ke Li, Sunghoon Ivan Lee, et al.. (2022). Toward Wide-Area Contactless Wireless Sensing. IEEE/ACM Transactions on Networking. 31(2). 590–605. 2 indexed citations
12.
Liu, Yunda, et al.. (2022). A Kinematic Data-Driven Approach to Differentiate Involuntary Choreic Movements in Individuals With Neurological Conditions. IEEE Transactions on Biomedical Engineering. 69(12). 3784–3791. 6 indexed citations
13.
Mirzadeh, Seyed Iman, et al.. (2021). LIDS: Mobile System to Monitor Type and Volume of Liquid Intake. IEEE Sensors Journal. 21(18). 20750–20763. 3 indexed citations
14.
Yin, Yuqing, et al.. (2021). Ubiquitous Smartphone-Based Respiration Sensing With Wi-Fi Signal. IEEE Internet of Things Journal. 9(2). 1479–1490. 29 indexed citations
15.
16.
Lee, Sunghoon Ivan, Catherine Adans-Dester, Anne O’Brien, et al.. (2020). Predicting and Monitoring Upper-Limb Rehabilitation Outcomes Using Clinical and Wearable Sensor Data in Brain Injury Survivors. IEEE Transactions on Biomedical Engineering. 68(6). 1871–1881. 31 indexed citations
17.
Mahyar, Narges, et al.. (2020). Rehabilitation Games in Real-World Clinical Settings. ACM Transactions on Computer-Human Interaction. 27(6). 1–43. 14 indexed citations
18.
Daneault, Jean‐François, et al.. (2020). A Simple Low-Cost Wearable Sensor for Long-Term Ambulatory Monitoring of Knee Joint Kinematics. IEEE Transactions on Biomedical Engineering. 67(12). 3483–3490. 17 indexed citations
19.
Lee, Sunghoon Ivan, et al.. (2019). A novel upper-limb function measure derived from finger-worn sensor data collected in a free-living setting. PLoS ONE. 14(3). e0212484–e0212484. 34 indexed citations
20.
Bonato, Paolo, et al.. (2018). The Use of a Finger-Worn Accelerometer for Monitoring of Hand Use in Ambulatory Settings. IEEE Journal of Biomedical and Health Informatics. 23(2). 599–606. 31 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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